most citedImplicit Inversion turns CLIP into a Decoder

1 citations · 1 across the 9 of their papers we have counts for

collaborators

10 papers

cs.CV2026

Cross-Modal Attention Acts as a Frequency Filter: Why Verbose Prompts Improve Robustness in Vision-Language Models

Farooq Ahmad Wani, Maria Sofia Bucarelli, Mujtaba Hussain Mirza +5

Vision-language models (VLMs) are fragile under image corruption. We find that the wording of the question affects VLMs in two opposite ways. Verbose questions make VLMs substantia…

cs.CR2026

Architectural Backdoors in Vision-Language Model Supply Chains via Representation Steering

Maria Rosaria Briglia, Igor Maljkovic, Antonio Emanuele Cinà +3

Vision--Language Models (VLMs) are increasingly deployed through a model supply chain in which pretrained checkpoints, architecture definitions, text encoders, and exported computa…

cs.LG2026

Steering Vectors are an Adversarial Attack Surface

Abzal Aidakhmetov, Donato Crisostomi, Tommaso Mencattini +3

Activation steering has become a popular way to control Large Language Model (LLM) behavior without fine-tuning. Since the technique is plug-and-play, users share datasets and prec…

cs.CR2026

Harnessing Hyperbolic Geometry for Harmful Prompt Detection and Sanitization

Igor Maljkovic, Maria Rosaria Briglia, Iacopo Masi +2

Vision-Language Models (VLMs) have become essential for tasks such as image synthesis, captioning, and retrieval by aligning textual and visual information in a shared embedding sp…

cs.LG2026

Not All Latent Spaces Are Flat: Hyperbolic Concept Control

Maria Rosaria Briglia, Simone Facchiano, Paolo Cursi +6

As modern text-to-image (T2I) models draw closer to synthesizing highly realistic content, the threat of unsafe content generation grows, and it becomes paramount to exercise contr…

cs.CL2026

Multi-objective Evolutionary Merging Enables Efficient Reasoning Models

Mario Iacobelli, Adrian Robert Minut, Tommaso Mencattini +4

Reasoning models achieve strong performance on complex problems by leveraging long chains of thought, but this deliberate reasoning incurs substantial inference-time cost. The Long…

cs.CV2026

A Provable Energy-Guided Test-Time Defense Boosting Adversarial Robustness of Large Vision-Language Models

Mujtaba Hussain Mirza, Antonio D'Orazio, Odelia Melamed +1

Despite the rapid progress in multimodal models and Large Visual-Language Models (LVLM), they remain highly susceptible to adversarial perturbations, raising serious concerns about…

cs.AI2026

Spilled Energy in Large Language Models

Adrian Robert Minut, Hazem Dewidar, Iacopo Masi

We reinterpret the final Large Language Model (LLM) softmax classifier as an Energy-Based Model (EBM), decomposing the sequence-to-sequence probability chain into multiple interact…

cs.CV2025★ 1 cited

Implicit Inversion turns CLIP into a Decoder

Antonio D'Orazio, Maria Rosaria Briglia, Donato Crisostomi +3

CLIP is a discriminative model trained to align images and text in a shared embedding space. Due to its multimodal structure, it serves as the backbone of many generative pipelines…

cs.LG2025

MASS: MoErging through Adaptive Subspace Selection

Donato Crisostomi, Alessandro Zirilli, Antonio Andrea Gargiulo +5

Model merging has recently emerged as a lightweight alternative to ensembling, combining multiple fine-tuned models into a single set of parameters with no additional training over…